Search Results (10)

Modifications in leaf architecture disrupt optical properties and internal light-scattering dynamics. Accurate modeling of leaf-scale light scattering is therefore essential not only for understanding how disease affects the availability of light for chlorophyll absorption, but also for evaluating its potential as an early optical marker for plant disease detection prior to visible symptom development. Conventional ray-tracing and radiative-transfer models rely on high-frequency approximations and thus fail to capture diffraction and coherent multiple-scattering effects when internal leaf structures are comparable to optical wavelengths. To overcome these limitations, we present a GPU-accelerated finite-difference time-domain (FDTD) framework for full-wave simulation of light propagation within plant leaves, using anatomically realistic dicot and monocot leaf cross-section geometries. Microscopic images acquired from publicly available sources were segmented into distinct tissue regions and assigned wavelength-dependent complex refractive indices to construct realistic electromagnetic models. The proposed FDTD framework successfully reproduced characteristic reflectance and transmittance spectra of healthy leaves across the visible and near-infrared (NIR) ranges. Quantitative agreement between the FDTD-computed spectral reflectance and transmittance and those predicted by the reference PROSPECT leaf optical model was evaluated using Lin’s concordance correlation coefficient. Higher concordance was observed for dicot leaves ($C_b=0.90$) than for monocot leaves ($C_b=0.79$), indicating a stronger agreement for anatomically complex dicot structures. Furthermore, simulations mimicking an early-stage fungal infection in a dicot leaf—modeled by the geometric introduction of melanized hyphae penetrating the cuticle and upper epidermis—revealed a pronounced reduction in visible green reflectance and a strong suppression of the NIR reflectance plateau. These trends are consistent with experimental observations reported in previous studies. Overall, this proof-of-concept study represents the first full-wave FDTD-based optical modeling of internal light scattering in plant leaves. The proposed framework enables direct electromagnetic analysis of pre- and post-penetration light-scattering dynamics during early fungal infection and establishes a foundation for exploiting leaf-scale light scattering as a next-generation, pre-symptomatic diagnostic indicator for plant fungal diseases. Full article

Breast cancer remains a leading cause of cancer-related deaths among women, emphasizing the critical need for early detection and monitoring techniques. Conventional imaging modalities such as mammography, MRI, and ultrasound have face sensitivity, specificity, cost, and patient comfort limitations. This study introduces a handheld Near-Infrared Diffuse Optical Tomography (NIR DOT) probe for breast cancer imaging. The NIRscan probe utilizes multi-wavelength light-emitting diodes (LEDs) and a linear charge-coupled device (CCD) sensor to acquire real-time optical data, reconstructing cross-sectional images of breast tissue based on scattering and absorption coefficients. With wavelengths optimized for the differential optical properties of tissue components, the probe enables functional imaging, distinguishing between healthy and malignant tissues. Clinical evaluations have demonstrated its potential for precise tumor localization and monitoring therapeutic responses, achieving a sensitivity of 94.7% and specificity of 84.2%. By incorporating machine learning algorithms and a modified diffusion equation (MDE), the system enhances the accuracy and speed of image reconstruction, supporting rapid, non-invasive diagnostics. This development represents a significant step forward in portable, cost-effective solutions for breast cancer detection, with potential applications in low-resource settings and diverse clinical environments. Full article

Compton scattering imaging with intense, high-energy synchrotron X-rays allows us to visualize a light element substance in an operating electrochemical device. In this paper, we report the first experiment of Compton scattering imaging (CSI) on an operating polymer electrolyte fuel cell (PEFC). The novelty of the CSI technique is a non-destructive direct observation of cross-sectional images with a sensitivity to light elements and a capability of simultaneous measurements with fluorescent X-rays of heavy elements. Analyses of the observed images provide the cross-sectional distribution of generated liquid water and its current density dependency. The results show that the amount of generated water increases in the vicinity of the cathode catalyst layer at current densities ranging from 100 to 500 mA/cm², while it remains constant or slightly decreases from 500 to 900 mA/cm². In both the gas diffusion layer and the channel, liquid water is observed near the channel and rib interface above 500 mA/cm², indicating the formation of a liquid water flow path. In addition, simultaneous measurements of fluorescent Pt-Ka X-rays reveal a significant correlation between the generated liquid water and Pt catalysts, using the Pearson correlation coefficient. The result shows that water is dispersed in the catalyst layer without any correlation with the amount of Pt catalysts at low current densities, but water tends to be distributed in the Pt-rich areas at high current densities. This study demonstrates that Compton scattering imaging is one of the unique techniques to characterize the behavior of generated liquid water in an operating PEFC. Full article

Extremely weak lidar reflections in the thermosphere, which correlate with ionosonde data, were detected in 2008 and 2017 over Kamchatka during seasons of low aerosol filling of the atmosphere at solar activity minima. Here, these reflections are considered in comparison with mesospheric and stratospheric lidar signals that makes it possible to determine favorable conditions for thermospheric lidar observations. In 2014, it was shown that lines of transitions between the excited states of atomic nitrogen ions fall within the 532 nm lidar signal emission band, and in 2017, lidar reflections in the thermosphere were simultaneously obtained at 561 and 532 nm excited transitions of atomic oxygen and nitrogen ions, thereby the resonant nature of thermospheric lidar reflections was established and confirmed. Here, using lidar signals at wavelengths of 561 and 532 nm in the altitude range of 30–400 km, by solving the inverse problem, we restore the light scattering coefficients corresponding to these wavelengths that makes it possible to compare the optical characteristics of the thermosphere, mesosphere, and upper stratosphere and to determine the relationship between resonant, Rayleigh, and aerosol light scattering at different heights of the atmosphere. In conclusion, using the scattering coefficients in the thermosphere, we find the cross-sections of light scattering at the 561 and 532 nm transitions of atomic oxygen and nitrogen ions and explain why the scattering coefficients for O${}^{+}$, 561 nm are less than for N${}^{+}$, 532 nm, while the concentration of O${}^{+}$ is two orders of magnitude higher than N${}^{+}$. The results obtained here are of interest for understanding the ionization effect of solar activity on the optical characteristics of the atmosphere that determine weather and climate changes. Full article

Particle size distribution (PSD), which is an important characteristic of marine suspended particles, plays a role in how light transfers in the ocean and impacts the ocean’s inherent optical properties (IOPs). However, PSD properties and the correlations with IOPs are rarely reported in coastal waters with complex optical properties. This study investigated the PSD variabilities both for the surface water and the water in vertical planes, and the correlations between PSD and the backscattering coefficient (b_bp), scattering coefficient (b_p), and attenuation coefficient (c_p), based on in situ PSD observations (within a size range of 2.05–297 μm) and IOPs in the coastal northern South China Sea. The results show a large variety of PSDs, with a range of 41.06–263.02 μm for the median particle diameter (D_v⁵⁰) and a range of 2.61–3.74 for the PSD slope. In addition, the predominance of small particles is most likely to appear in the nearshore shallow water and estuaries with a large amount of sediment discharge, and vice versa. For the variabilities of IOPs, the particle concentration in a cross-sectional area (AC) is the first driving factor of the variations of b_bp, b_p, and c_p, and the product of the mean particle diameter (D_A) and the apparent density (ρ_a) can explain most variations of the mass-specific b_bp (b_bp/SPM), b_p (b_p/SPM), and c_p (c_p/SPM). In this study, we found that particle size is strongly correlated with volume-specific b_bp (b_bp/VC), b_p (b_p/VC), and c_p (c_p/VC), and the 10th percentile diameter of the accumulated volume concentration (D_v¹⁰) can better explain the variations of b_bp/VC. These findings suggest a potential PSD retrieval method utilizing the b_bp or b_p, which may be determined by remote sensing observations. Full article

An efficiency droop in GaN-based light-emitting diodes (LED) was characterized by examining its general thermophysical parameters. An effective suppression of emission degradation afforded by the introduction of InGaN/GaN heterobarrier structures in the active region was attributable to an increase in the capture cross-section ratios. The Debye temperatures and the electron–phonon interaction coupling coefficients were obtained from temperature-dependent current-voltage measurements of InGaN/GaN multiple-quantum-well LEDs over a temperature range from 20 to 300 K. It was found that the Debye temperature of the LEDs was modulated by the InN molar fraction in the heterobarriers. As far as the phonons involved in the electron–phonon scattering process are concerned, the average number of phonons decreases with the Debye temperature, and the electron–phonon interaction coupling coefficients phenomenologically reflect the nonradiative transition rates. We can use the characteristic ratio of the Debye temperature to the coupling coefficient (DCR) to assess the efficiency droop phenomenon. Our investigation showed that DCR is correlated to quantum efficiency (QE). The light emission results exhibited the high and low QEs to be represented by the high and low DCRs associated with low and high injection currents, respectively. The DCR can be envisioned as a thermophysical marker of LED performance, not only for efficiency droop characterization but also for heterodevice structure optimization. Full article

Mass absorption cross-section of black carbon (MAC_BC) describes the absorptive cross-section per unit mass of black carbon, and is, thus, an essential parameter to estimate the radiative forcing of black carbon. Many studies have sought to estimate MAC_BC from a theoretical perspective, but these studies require the knowledge of a set of aerosol properties, which are difficult and/or labor-intensive to measure. We therefore investigate the ability of seven data analytical approaches (including different multivariate regressions, support vector machine, and neural networks) in predicting MAC_BC for both ambient and biomass burning measurements. Our model utilizes multi-wavelength light absorption and scattering as well as the aerosol size distributions as input variables to predict MAC_BC across different wavelengths. We assessed the applicability of the proposed approaches in estimating MAC_BC using different statistical metrics (such as coefficient of determination (R²), mean square error (MSE), fractional error, and fractional bias). Overall, the approaches used in this study can estimate MAC_BC appropriately, but the prediction performance varies across approaches and atmospheric environments. Based on an uncertainty evaluation of our models and the empirical and theoretical approaches to predict MAC_BC, we preliminarily put forth support vector machine (SVM) as a recommended data analytical technique for use. We provide an operational tool built with the approaches presented in this paper to facilitate this procedure for future users. Full article

Archon2 is a fluorescent voltage sensor derived from Archaerhodopsin 3 (Arch) of Halorubrum sodomense using robotic multidimensional directed evolution approach. Here we report absorption and emission spectroscopic studies of Archon2 in Tris buffer at pH 8. Absorption cross-section spectra, fluorescence quantum distributions, fluorescence quantum yields, and fluorescence excitation spectra were determined. The thermal stability of Archon2 was studied by long-time attenuation coefficient measurements at room temperature (21 ± 1 °C) and at refrigerator temperature (3 ± 1 °C). The apparent melting temperature was determined by stepwise sample heating up and cooling down (obtained apparent melting temperature: 63 ± 3 °C). In the protein melting process protonated retinal Schiff base (PRSB) with absorption maximum at 586 nm converted to de-protonated retinal Schiff base (RSB) with absorption maximum at 380 nm. Storage of Archon2 at room temperature and refrigerator temperature caused absorption coefficient decrease because of partial protein clustering to aggregates at condensation nuclei and sedimentation. At room temperature an onset of light scattering was observed after two days because of the beginning of protein unfolding. During the period of observation (18 days at 21 °C, 22 days at 3 °C) no change of retinal isomer composition was observed indicating a high potential energy barrier of S₀ ground-state isomerization. Full article

Fluorescence-guided surgery is a state-of-the-art approach for intraoperative imaging during neurosurgical removal of tumor tissue. While the visualization of high-grade gliomas is reliable, lower grade glioma often lack visible fluorescence signals. Here, we present a hybrid prototype combining visible light optical coherence microscopy (OCM) and high-resolution fluorescence imaging for assessment of brain tumor samples acquired by 5-aminolevulinic acid (5-ALA) fluorescence-guided surgery. OCM provides high-resolution information of the inherent tissue scattering and absorption properties of tissue. We here explore quantitative attenuation coefficients derived from volumetric OCM intensity data and quantitative high-resolution 5-ALA fluorescence as potential biomarkers for tissue malignancy including otherwise difficult-to-assess low-grade glioma. We validate our findings against the gold standard histology and use attenuation and fluorescence intensity measures to differentiate between tumor core, infiltrative zone and adjacent brain tissue. Using large field-of-view scans acquired by a near-infrared swept-source optical coherence tomography setup, we provide initial assessments of tumor heterogeneity. Finally, we use cross-sectional OCM images to train a convolutional neural network that discriminates tumor from non-tumor tissue with an accuracy of 97%. Collectively, the present hybrid approach offers potential to translate into an in vivo imaging setup for substantially improved intraoperative guidance of brain tumor surgeries. Full article

CdSe/ZnS quantum-dot-converted elements (QDCEs) are good candidates for substituting rare-earth phosphor-converted elements (PCEs) in white light-emitting diodes (LEDs); however, studies on their scattering and absorption properties are scarce, suppressing further increment in the optical and thermal performance of quantum-dot-converted LEDs. Therefore, we introduce the finite-difference time-domain (FDTD) method to achieve the critical optical parameters of QDCEs when used in white LEDs; their scattering cross-section (coefficient), absorption cross-section (coefficient), and scattering phase distributions are presented and compared with those of traditional YAG phosphor-converted elements (PCEs) at varying particle size and concentration. At a commonly used concentration ( $<50\mathrm{mg}/{\mathrm{cm}}^3$ ), QDCEs exhibit stronger absorption (tens of millimeters, even for green-to-red-wavelength light) and weaker scattering ( $<1{\mathrm{mm}}^{-1}$ ) compared to PCEs; the reabsorption, total internal reflection, angular uniformity, and thermal quenching would be more significant concerns for QDCEs. Therefore, the unique scattering and absorption properties of QDCEs should be considered when used in white LEDs. Furthermore, knowledge of these important optical parameters is helpful for beginning a theoretical study on quantum-dot-converted LEDs according to the ray tracing method. Full article